| Title |
Assessing and Predicting Changes of the Ecosystem Service Values Based on Land Use/Land Cover Changes With a Random Forest-Cellular Automata Model in Qingdao Metropolitan Region, China |
| ID_Doc |
66280 |
| Authors |
Qin, XC; Fu, BH |
| Title |
Assessing and Predicting Changes of the Ecosystem Service Values Based on Land Use/Land Cover Changes With a Random Forest-Cellular Automata Model in Qingdao Metropolitan Region, China |
| Year |
2020 |
| Published |
|
| DOI |
10.1109/JSTARS.2020.3029712 |
| Abstract |
With the rapid development of economy, the land use/land cover (LULC) in Qingdao Metropolitan Region had undergone tremendous changes, thus causing negative effects on ecosystem functions and services. Based on the analyses of remote sensing images and statistical yearbook data, the ecosystem service value (ESV) was quantitative monetary accounted by using the equivalent factor method, and the impact of LULC on ecosystem services was analyzed. A random forest-cellular automata (RF-CA) model and the multiscenario simulation were employed to forecast the LULC changes for 2032. Our results showed that the total ESV of Qingdao Metropolitan Region decreased from 26.17 billion RMB in 1990 to 20.86 billion RMB in 2017. Based on the validation of RF-CA model, the total ESV in 2032 might continuously decline compared with that in 2017, while the ESV under ecological protection priority scenario was higher than business-as-usual scenario. The reduction of ESV was mainly caused by the LULC changes, such as the loss of land with high ecological value. This research provided the useful information for the intensive utilization of land resources and the sustainable development of ecological environment in Qingdao Metropolitan Region. |
| Author Keywords |
Ecosystems; Biological system modeling; Predictive models; Economics; Automata; Sea measurements; Urban areas; Cellular automata (CA); ecosystem service value (ESV); land use; land cover (LULC) change; Qingdao Metropolitan Region |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000597143300003 |
| WoS Category |
Engineering, Electrical & Electronic; Geography, Physical; Remote Sensing; Imaging Science & Photographic Technology |
| Research Area |
Engineering; Physical Geography; Remote Sensing; Imaging Science & Photographic Technology |
| PDF |
https://ieeexplore.ieee.org/ielx7/4609443/4609444/09268450.pdf
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